KE Sharquie, HA Hassan, AA Noaimi, IRAQI JOURNAL OF COMMUNITY MEDICINE, 2010

Background: Although various imaging modalities are available for evaluating suspicious breast lesions, ultrasound-based Shear-Wave Elastography (SWE) is an advanced, non-invasive technique complementary to grayscale sonography. This technique evaluates the elasticity of a specific tissue by applying sonic pressure to that tissue.

Objective: The aim is to assess the role of SWE in evaluating solid breast masses in correlation to histopathological study results.

Subjects and Methods: This prospective study was done in a tertiary care teaching hospital from September 2019 to August 2020. A study population of 50 women aged 18 years or above with an

Epithelial mesenchymal transition (EMT) is a process comprising cellular and molecular events which result in cells shifting from an epithelial to a mesenchymal phenotype. Periodontitis is a destructive chronic disease of the periodontium initiated in response to a dysbiotic microbiome, and dominated by Gram-negative bacteria in the subgingival niches accompanied by an aberrant immune response in susceptible subjects. Both EMT and periodontitis share common risk factors and drivers, including Gram-negative bacteria, excess inflammatory cytokine production, smoking, oxidative stress and diabetes mellitus. In addition, periodontitis is characterized by down-regulation of key epithelial markers such as E-cadherin together with up-regulation of

Background: Treatment of invasive prolactinoma, which has several characteristics including invasive growth into cavernous sinuses and formation of giant adenomas compressing adjacent neural structures, resulting in neurological dysfunction, has been very challenging. There are relatively few reports available describing long-term treatment outcome.

Aims of the study: In this study we evaluate the results of cabergoline administration as initial treatment during 4 years follow up period.

Methods: We prospectively categorized 36 patients into four groups according to the results of 3 months of cabergoline treatment: group 1, tumor volume reduction (TVR) ˃25% with normaliz

Background: Blastocystis spp. distributes world widely and the genus Blastocystis include many subtypes that are isolated from human intestinal tract. It is considered the most common parasite detected in human being.

Objectives: To evaluate the incidence of Blastocystis spp. among leukemic children, to find out its association with the presence of symptoms (diarrhea and abdominal pain), and to assess the efficacy of different staining methods in detection of Blastocystis spp. 

Type of the study: cross-sectional study.

Method: 103 children were enrolled in this study, 53 leukemic patients and 50 healthy con

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class

Image classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class